Review Publications

The rapid expansion of transcriptomics and affordability of next-generation sequencing (NGS) technologies generate rocketing amounts of gene expression data across biology and medicine, including...

Alternative splicing (AS) is an essential component of gene expression regulation that contributes to the diversity of proteomes. Recent developments in RNA sequencing (RNA-seq) technologies, combined...

The importance of diversity and cellular specialization is clear for many reasons, from population-level diversification, to improved resiliency to unforeseen stresses, to unique functions within...

The immune system is composed of a complex hierarchy of cell types that protect the organism against disease and maintain homeostasis. Identifying heterogeneity of immune cells is the...

For the last 40 years, “Sanger sequencing” allowed to unveil crucial secrets of life. However, this method of sequencing has been time-consuming, laborious and remains expensive even today. Human...

Single-cell RNA sequencing (scRNA-seq) allows researchers to collect large catalogues detailing the transcriptomes of individual cells. Unsupervised clustering is of central importance for the analysis of these data, as it is used to identify putative cell types...

High-throughput next-generation sequencing technologies have led to a rapid increase in the number of sequence variants identified in clinical practice via diagnostic genetic tests. Current bioinformatic analysis pipelines fail to take adequate account...

Ribose methylation is one of the most abundant RNA modifications and is found in all domains of life and all major classes of RNA (rRNA, tRNA, and mRNA)...

Transcriptome profiling has become routine in studies of many biological processes. However, favored approaches such as short-read Illumina RNA sequencing are giving way to long-read sequencing platforms better suited to interrogating the complex...

Subpopulation identification, usually via some form of unsupervised clustering, is a fundamental step in the analysis of many single-cell RNA-seq data sets. This has motivated the development and application of a broad range of clustering methods, based on various..